Maggie Myers

Dr. Maggie Myers has established herself as a distinguished educator and researcher at the University of Texas at Austin, where she served as a lecturer in both the Department of Computer Science and the Department of Statistics and Data Sciences. Her expertise spans probability and Bayesian statistical methods, mathematics education, curriculum development, informal learning, and formal derivation of algorithms. Throughout her career, she has made significant contributions to both education and research, co-authoring important works including "Linear Algebra: Foundations to Frontiers" and "The Science of Deriving Dense Linear Algebra Algorithms." Her earlier career included roles as a senior research scientist with the Charles A. Dana Center and consultant to the Southwest Educational Development Lab (SEDL). Her teaching portfolio encompasses undergraduate and graduate courses in Bayesian Statistics, while her research activities range from informal learning opportunities in mathematics education to formal derivation of linear algebra algorithms. Her innovative work in educational development, including the creation of MOOCs and comprehensive electronic textbooks, earned her the 2015 CNS Teaching Award. Her ongoing collaboration with Prof. van de Geijn, both in marriage and research, has produced numerous significant contributions to the field of high-performance computing and mathematics education.